a16z Podcast | Machine Intelligence, from University to Industry
Skills:
Agent Foundations90%Tool Use & Function Calling80%Multi-Agent Systems70%Autonomous Workflows60%ML Maths Basics50%
From the significance of Google DeepMind's AlphaGo wins to recent advances in "expert-level artificial intelligence" in playing an imperfect/ asymmetric information game like poker, toys and games have played and continue to play a critical role in advancing machine intelligence.
One of the pioneers in this area among others is the Alberta Innovates Centre for Machine Learning -- now the Alberta Machine Intelligence Institute (amii) -- which in 2007 solved the long-standing challenge of checkers, and in 2015 produced the first AI agent capable of playing "an essentially perfect game" of heads-up limit hold’em poker. But what does that mean for the evolution of such technology out of play and into production? Out of universities and into industry? (Especially when many such university programs and talent are being hollowed out by companies and they're reliant on intellectual property or provincial support, as is the case of this University of Alberta based institute). And how can CEOs and others embrace learning about this tech somewhere in between?
So... what will it take to make AI "real"? What about genetic algorithms, treating computers like people, and other near- and far-future possibilities? This episode featuring the executive director of Amii, Cameron Schuler, and a16z deal, research, and investing team operating head Frank Chen covers all this and more. The conversation was recorded recently as part of our inaugural a16z Summit event.
image: Nyks / Wikimedia Commons
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